2.2k citations
- Cornell UniversityUS13 papers
- Stony Brook UniversityUS11 papers
- Harvard UniversityUS10 papers
- Emory UniversityUS8 papers
- City College of New YorkUS7 papers
- Weill Cornell MedicineUS7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Columbia UniversityUS6 papers
- Johns Hopkins UniversityUS6 papers
- Queen's UniversityCA6 papers
- The University of Texas MD Anderson Cancer CenterUS6 papers
- Tri-Institutional PhD Program in Chemical BiologyUS6 papers
162 papers
Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction
Mojtaba Safari, Shansong Wang, Zach Eidex +4
Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantitative analysis. Existing deep l…
On the Role of Calibration in Benchmarking Algorithmic Fairness for Skin Cancer Detection
Brandon Dominique, Prudence Lam, Nicholas Kurtansky +4
Artificial Intelligence (AI) models have demonstrated expert-level performance in melanoma detection, yet their clinical adoption is hindered by performance disparities across demo…
Systematic Review and Meta-analysis of AI-driven MRI Motion Artifact Detection and Correction
Mojtaba Safari, Zach Eidex, Richard L. J. Qiu +3
Background: To systematically review and perform a meta-analysis of artificial intelligence (AI)-driven methods for detecting and correcting magnetic resonance imaging (MRI) motion…
Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence
Maximilian Ferle, Jonas Ader, Thomas Wiemers +7
Risk stratification is a key tool in clinical decision-making, yet current approaches often fail to translate sophisticated survival analysis into actionable clinical criteria. We…
Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion
Jorge Tapias Gomez, Nishant Nadkarni, Lando S. Bosma +7
Objective: Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging…
Black Older Adults' Perception of Using Voice Assistants to Enact a Medical Recovery Curriculum
Andrea Green, Gabrielle Polite, Isabelle Hung +4
The use of interactive voice assistants (IVAs) in healthcare provides an avenue to address diverse health needs, such as gaps in the medical recovery period for older adult patient…